Faming Liang

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 43

Top Topics

Brain Connectivity

Stochastic Gradient

Top Venues

Publications

Yaxin Fang, Faming Liang
Causal-StoNet: Causal Inference for High-Dimensional Complex Data. CoRR (2024)
Faming Liang, Sehwan Kim, Yan Sun
Extended Fiducial Inference: Toward an Automated Process of Statistical Inference. CoRR (2024)
Yaxin Fang, Faming Liang
Causal-StoNet: Causal Inference for High-Dimensional Complex Data. ICLR (2024)
Frank Shih, Faming Liang
Fast Value Tracking for Deep Reinforcement Learning. ICLR (2024)
Frank Shih, Faming Liang
Fast Value Tracking for Deep Reinforcement Learning. CoRR (2024)
Tianning Dong, Yan Sun, Faming Liang
Deep network embedding with dimension selection. Neural Networks 179 (2024)
Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
Non-reversible Parallel Tempering for Deep Posterior Approximation. AAAI (2023)
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang
PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols. ACM Comput. Surv. 55 (2) (2023)
Mingxuan Zhang, Yan Sun, Faming Liang
Sparse Deep Learning for Time Series Data: Theory and Applications. CoRR (2023)
Sehwan Kim, Qifan Song, Faming Liang
A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules. CoRR (2023)
Mingxuan Zhang, Yan Sun, Faming Liang
Sparse Deep Learning for Time Series Data: Theory and Applications. NeurIPS (2023)
Tianning Dong, Peiyi Zhang, Faming Liang
A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters. J. Comput. Graph. Stat. 32 (2) (2023)
Siqi Liang, Yan Sun, Faming Liang
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network. CoRR (2022)
Yan Sun, Faming Liang
A Kernel-Expanded Stochastic Neural Network. CoRR (2022)
Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR (2022)
Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR (2022)
Wei Deng, Guang Lin, Faming Liang
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization. Stat. Comput. 32 (4) (2022)
Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
Non-reversible Parallel Tempering for Deep Posterior Approximation. CoRR (2022)
Siqi Liang, Yan Sun, Faming Liang
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network. NeurIPS (2022)
Yan Sun, Qifan Song, Faming Liang
Consistent Sparse Deep Learning: Theory and Computation. CoRR (2021)
Yan Sun, Wenjun Xiong, Faming Liang
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration. CoRR (2021)
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. ICLR (2021)
Yao Chen, Qingyi Gao, Faming Liang, Xiao Wang
Nonlinear Variable Selection via Deep Neural Networks. J. Comput. Graph. Stat. 30 (2) (2021)
Yan Sun, Wenjun Xiong, Faming Liang
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration. NeurIPS (2021)
Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. ICML (2020)
Qifan Song, Yan Sun, Mao Ye, Faming Liang
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection. CoRR (2020)
Wei Deng, Guang Lin, Faming Liang
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. CoRR (2020)
Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. CoRR (2020)
Wei Deng, Guang Lin, Faming Liang
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. NeurIPS (2020)
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang
PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols. CoRR (2020)
Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. CoRR (2020)
Sehwan Kim, Qifan Song, Faming Liang
Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts. CoRR (2020)
Aiying Zhang, Biao Cai, Wenxing Hu, Bochao Jia, Faming Liang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang
Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence. IEEE Trans. Medical Imaging 39 (2) (2020)
Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
An Adaptive Empirical Bayesian Method for Sparse Deep Learning. CoRR (2019)
Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
An Adaptive Empirical Bayesian Method for Sparse Deep Learning. NeurIPS (2019)
Jingnan Xue, Faming Liang
Double-Parallel Monte Carlo for Bayesian analysis of big data. Stat. Comput. 29 (1) (2019)
Suwa Xu, Bochao Jia, Faming Liang
Learning Moral Graphs in Construction of High-Dimensional Bayesian Networks for Mixed Data. Neural Comput. 31 (6) (2019)
Aiying Zhang, Jian Fang, Faming Liang, Vince D. Calhoun, Yu-Ping Wang
Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model. IEEE J. Biomed. Health Informatics 23 (4) (2019)
Tianzhou Ma, Faming Liang, Steffi Oesterreich, George C. Tseng
A Joint Bayesian Model for Integrating Microarray and RNA Sequencing Transcriptomic Data. J. Comput. Biol. 24 (7) (2017)
Georgios Karagiannis, Bledar A. Konomi, Guang Lin, Faming Liang
Parallel and interacting stochastic approximation annealing algorithms for global optimisation. Stat. Comput. 27 (4) (2017)
Donghyeon Yu, Johan Lim, Xinlei Wang, Faming Liang, Guanghua Xiao
Enhanced construction of gene regulatory networks using hub gene information. BMC Bioinform. 18 (1) (2017)
Faming Liang, Jinsu Kim, Qifan Song
A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data. Technometrics 58 (3) (2016)
Yichen Cheng, Faming Liang
Comment: "Modeling an Augmented Lagrangian for Blackbox Constrained Optimization" by Gramacy et al. Technometrics 58 (1) (2016)
Ick-Hoon Jin, Faming Liang
Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants. Comput. Stat. Data Anal. 71 (2014)
Sooyoung Cheon, Faming Liang, Yuguo Chen, Kai Yu
Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities. Stat. Comput. 24 (4) (2014)
Yichen Cheng, Xin Gao, Faming Liang
Bayesian Peak Picking for NMR Spectra. Genom. Proteom. Bioinform. 12 (1) (2014)
Faming Liang, Ick-Hoon Jin
A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants. Neural Comput. 25 (8) (2013)
Chen Zhou, Ping Yang, Andrew E. Dessler, Faming Liang
Statistical Properties of Horizontally Oriented Plates in Optically Thick Clouds From Satellite Observations. IEEE Geosci. Remote. Sens. Lett. 10 (5) (2013)
Sooyoung Cheon, Faming Liang
Folding small proteins via annealing stochastic approximation Monte Carlo. Biosyst. 105 (3) (2011)
Faming Liang
Annealing evolutionary stochastic approximation Monte Carlo for global optimization. Stat. Comput. 21 (3) (2011)
G. Peter Zhang, Craig A. Hill, Yusen Xia, Faming Liang
Modeling the Relationship Between EDI Implementation and Firm Performance Improvement With Neural Networks. IEEE Trans Autom. Sci. Eng. 7 (1) (2010)
Qianxing Mo, Faming Liang
A hidden Ising model for ChIP-chip data analysis. Bioinform. 26 (6) (2010)
Mingqi Wu, Faming Liang, Yanan Tian
Bayesian modeling of ChIP-chip data using latent variables. BMC Bioinform. 10 (2009)
Faming Liang, Jian Zhang
Learning Bayesian networks for discrete data. Comput. Stat. Data Anal. 53 (4) (2009)
Yuan Ren, Yu Ding, Faming Liang
Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems. Stat. Comput. 18 (4) (2008)
Sooyoung Cheon, Faming Liang
Phylogenetic tree construction using sequential stochastic approximation Monte Carlo. Biosyst. 91 (1) (2008)
Faming Liang
Annealing stochastic approximation Monte Carlo algorithm for neural network training. Mach. Learn. 68 (3) (2007)
Faming Liang, Naisyin Wang
Dynamic agglomerative clustering of gene expression profiles. Pattern Recognit. Lett. 28 (9) (2007)
Faming Liang
Use of SVD-based probit transformation in clustering gene expression profiles. Comput. Stat. Data Anal. 51 (12) (2007)
Faming Liang, Jianhua Huang
Statistical and Computational Inverse Problems. Technometrics 48 (1) (2006)
Faming Liang, Chuanhai Liu
Efficient MCMC estimation of discrete distributions. Comput. Stat. Data Anal. 49 (4) (2005)
Faming Liang
Bayesian neural networks for nonlinear time series forecasting. Stat. Comput. 15 (1) (2005)
Faming Liang
Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo. Neural Comput. 17 (6) (2005)
Faming Liang
An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine. Neural Comput. 15 (8) (2003)
Jason Cong, Tianming Kong, Faming Liang, Jun S. Liu, Wing Hung Wong, Dongmin Xu
Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application. ASP-DAC (2000)
Jason Cong, Tianming Kong, Dongmin Xu, Faming Liang, Jun S. Liu, Wing Hung Wong
Relaxed Simulated Tempering for VLSI Floorplan Designs. ASP-DAC (1999)